Spark 提交任务详解
2016-12-09 17:18
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Running Spark on YARN
cluster mode :
client mode :
实际案例:在YARN模式,executor-cores和executor-memory的设置对调度计算机的性能作用很重要
spark-submit 参数详解:
Spark standalone with cluster deploy mode only:
Spark standalone or Mesos with cluster deploy mode only:
Spark standalone and Mesos only:
==Spark standalone and YARN only:==
YARN-only:
cluster mode :
$ ./bin/spark-submit --class org.apache.spark.examples.SparkPi \ --master yarn \ --deploy-mode cluster \ --driver-memory 4g \ --executor-memory 2g \ --executor-cores 1 \ lib/spark-examples*.jar \ 10
client mode :
$ ./bin/spark-submit --class org.apache.spark.examples.SparkPi \ --master yarn \ --deploy-mode client \ --driver-memory 4g \ --executor-memory 2g \ --executor-cores 1 \ lib/spark-examples*.jar \ 10
实际案例:在YARN模式,executor-cores和executor-memory的设置对调度计算机的性能作用很重要
$ ./bin/spark-submit \ --class cn.cstor.face.BatchCompare \ --master yarn \ --deploy-mode client \ --executor-memory 30G \ --executor-cores 20 \ --properties-file $BIN_DIR/conf/cstor-spark.properties \ cstor-deep-1.0-SNAPSHOT.jar
spark-submit 参数详解:
[root@datacube201 work]# ../bin/spark-submit Usage: spark-submit [options] <app jar | python file> [app arguments] Usage: spark-submit --kill [submission ID] --master [spark://...] Usage: spark-submit --status [submission ID] --master [spark://...] Options: --master MASTER_URL spark://host:port, mesos://host:port, yarn, or local. --deploy-mode DEPLOY_MODE Whether to launch the driver program locally ("client") or on one of the worker machines inside the cluster ("cluster") (Default: client). --class CLASS_NAME Your application's main class (for Java / Scala apps). --name NAME A name of 4000 your application. --jars JARS Comma-separated list of local jars to include on the driver and executor classpaths. --packages Comma-separated list of maven coordinates of jars to include on the driver and executor classpaths. Will search the local maven repo, then maven central and any additional remote repositories given by --repositories. The format for the coordinates should be groupId:artifactId:version. --exclude-packages Comma-separated list of groupId:artifactId, to exclude while resolving the dependencies provided in --packages to avoid dependency conflicts. --repositories Comma-separated list of additional remote repositories to search for the maven coordinates given with --packages. --py-files PY_FILES Comma-separated list of .zip, .egg, or .py files to place on the PYTHONPATH for Python apps. --files FILES Comma-separated list of files to be placed in the working directory of each executor. --conf PROP=VALUE --properties-file FILE 从文件中载入额外的配置,如果不指定则载入conf/spark-defaults.conf。 --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 1024M). --driver-java-options Extra Java options to pass to the driver. --driver-library-path Extra library path entries to pass to the driver. --driver-class-path Extra class path entries to pass to the driver. Note that jars added with --jars are automatically included in the classpath. --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G). --proxy-user NAME User to impersonate when submitting the application. --help, -h Show this help message and exit --verbose, -v Print additional debug output --version, Print the version of current Spark
Spark standalone with cluster deploy mode only:
--driver-cores NUM Cores for driver (Default: 1).
Spark standalone or Mesos with cluster deploy mode only:
--supervise If given, restarts the driver on failure. --kill SUBMISSION_ID If given, kills the driver specified. --status SUBMISSION_ID If given, requests the status of the driver specified.
Spark standalone and Mesos only:
--total-executor-cores NUM Total cores for all executors.
==Spark standalone and YARN only:==
--executor-cores NUM Number of cores per executor. (Default: 1 in YARN mode, or all available cores on the worker in standalone mode)
YARN-only:
Options: --driver-cores NUM driver使用的核心数,只在cluster模式使用,默认值为1。 --queue QUEUE_NAME 提交到指定的YARN队列,默认队列为"default"。 --num-executors NUM 启动的executor的数量,默认值为2. --archives ARCHIVES Comma separated list of archives to be extracted into the working directory of each executor. --principal PRINCIPAL Principal to be used to login to KDC, while running on secure HDFS. --keytab KEYTAB The full path to the file that contains the keytab for the principal specified above. This keytab will be copied to the node running the Application Master via the Secure Distributed Cache, for renewing the login tickets and the delegation tokens periodically.